Trust Experience (TX) Design
Our research is dedicated to the rigorous design of trusted customer relationships in data- and tech-intensive environments. We call this Trust Experience (TX) design, an entirely new discipline which will help professionalising the management of trust. We study and develop design principles and operational approaches that allow to
- Reduce uncertainty and the role of trustless technologies (e.g., blockchain)
- Reduce vulnerabilities of customers
- Increase confidence via trust signals (e.g., in the form of confidence-building statements in financial reports or published positive user experiences in platforms such as TrustPilot)
Further research projects are dedicated to essential prerequisites of trust management (trust governance, trust mining) as well as outcomes, extreme trust and return-on-trust.
Increase benevolence with specific practices (see ‘The Benevolent Enterprise’ paper)
In particular we research the following TX mechanisms:
Trust by Choice: Omni-Trust: Customers do not only select their preferred channel of interaction based on convenience, but also based on their individual trust assessments. For example, customers will choose their form of identification (loyalty-card, app-based, biometrics) that they trust the most in a specific context though it might not be the most convenient one. Omni-trust is dedicated to offering the right choice at such moments of trust and is an important extension of the dominating focus on omni-channel.
Trust by Acceptance: Real-World Cookie: Web cookies are by now an established entry point into online interactions. However, a corresponding, transparent point of accepting different intensities of tracking and personalisation does not exist for in-store experiences. In our related research, we design tech-enabled real-world cookies – on entering a store customers would be automatically WiFi-onboarded and can opt in. This way, they could choose the degree to which they like to engage with the retailer who in response tailors pricing, wayfinding or experience design for those trusting customers who are willing to share relevant data.
Trust by Individualisation: Trust Persona: Trust is a subjective assessment and as such differs between individuals. In our research on trust persona we develop archetypes for trust persona which can be differentiated based on their preferred trust signals (e.g, product reviews, expert assessments) and the comprehensiveness of their trust concerns. The latter might be narrowly centred on product qualities, also encompass related supply chain matters (e.g., carbon emissions) or include value-based assessment of the organisations providing the products. A deep understanding of the trust persona that matter allows organisations to tailor customer interactions to the very specific trust requirements of their customers (e.g., show expert reviews to those customers who research product features intensively). Further research projects are dedicated to essential prerequisites of trust management (trust governance, trust mining) as well as outcomes, extreme trust and return-on-trust.
Trust Governance: Organisations who are making trust a primary concern, will not only require the conscious design of trusted processes, but also new roles and responsibilities. In this research project, we study the profile and impact of dedicated roles such as Chief Trust Officers, Trust Experience (TX) Designers or Trust Architects.
Trust Mining: Organisations tend to have poor insights into the extent to which they are trusted. They either rely on third party, but highly aggregated surveys, engage in their own expensive manual data collection or use metrics (such as NPS) that are poor trust representations. Using the growing data footprint to derive indicators for customers’ trust has the potential to feed real-time trust dashboards and accelerate related decision making. In particular we study the potential of data and process mining as a source of such trust signals.
Extreme Trust: Extreme trust exists when we trust a provider more than ourselves. This is already the case in healthcare, but it is only starting to emerge in areas such as finance or retail. We study success and context factors for successful extreme trust leading to scenarios where grocery retailers, for example, would shop for their customers or banks offer algorithms that conduct financial transactions on behalf of their customers.
Return-on-Trust (RoT): Trust is not a means to an end. However, metrics that easily and efficiently illustrate the context-dependent correlation between trust and qualitative and quantitative outcomes are at infancy. Deepening our understanding of RoT creates confidence among executives in their decision making when it comes to balancing transactional and trust-based value propositions